PT - JOURNAL ARTICLE AU - Enrique Batiz-Zuk AU - George Christodoulakis AU - Ser-Huang Poon TI - Structural Credit Loss Distributions<br/>under Non-Normality AID - 10.3905/jfi.2013.23.1.056 DP - 2013 Jun 30 TA - The Journal of Fixed Income PG - 56--75 VI - 23 IP - 1 4099 - https://pm-research.com/content/23/1/56.short 4100 - https://pm-research.com/content/23/1/56.full AB - In the context of Merton [1974] and Vasicek [1987, 2002] Gaussian single-factor credit risk models, the authors examine the impact of neglected non-normality of the underlying asset return process on the shape of the derived credit loss distribution and the resulting Basel capital requirements. They relax the Gaussian assumption and specify skew-normal and skew-student t densities to model the underlying asset return process, thus generalizing the credit loss distribution, and develop a maximum-likelihood estimator for the structural parameters. They apply their approach to aggregate charge-off rates published by the Federal Reserve Board for 10 U.S. sectors.The authors show that the non-gaussian modeling of the common factor provides a better characterization of data than its Gaussian counterpart and that it has a significant impact on the capital requirements, depending on the sign and magnitude of the skew-related coefficient. On the other hand, the non-gaussian modeling of the idiosyncratic factor does not provide a significantly better characterization than the Gaussian base case. The latter could stem from the fact that the sector portfolios are large, so the idiosyncratic component has been diversified away.TOPICS: Analysis of individual factors/risk premia, quantitative methods